Disease Detection in the Age of Quantum Computing
summary
Claims a working pipeline that trains a hybrid classical–quantum classifier to detect sepsis, encoding patient features with a ZZ feature map and training a VQC on IBM Quantum hardware via Qiskit. It compresses ~140 features into four qubits using PCA, runs on real machines (not just simulators), finds ~100 sepsis cases in MIMIC 4, outputs a confusion matrix with precision/recall, and notes noise, limited qubits, and the need for error correction and larger benchmarks.
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chapters (8)
- 0:00Introduction
- 1:04Early disease detection benefits
- 3:52Quantum computing advantages
- 9:51Quantum disease detection
- 17:41Data preprocessing
- 22:00Quantum circuit design
- 27:23Code walkthrough
- 32:26Future enhancements
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